هوش مصنوعی در تحقیقات فارماکولوژی و کشف دارو
کد: G-1840
نویسندگان: Ramin Ataee * ℗, Parisa Saberi Hasanabadi
زمان بندی: زمان بندی نشده!
برچسب: کشف و طراحی دارو
دانلود: دانلود پوستر
خلاصه مقاله:
خلاصه مقاله
Background: In recent years artificial intelligence (AI), and especially machine learning (ML), has rapidly considered for pharmacology is a field of its' application where AI and ML approaches are particularly useful to analyze data according to different aspects as chemical structure to clinical informations from genomic to disease stages. For several days ,AI has being applied in drug discovery and identification of drug targets.Morever, AI models which help to describe an drug response of individuals are shown, which occupy from drug discovery to personalized medicine .In this review we explained some of these. Methods: By exploring some research data motors as Pubmed,Medline,Elsevier,Google Scolar,Ovids, we have assayed some AI practices and applications in Pharmacology .Results:More than 20 articles which describing use of AI in pharmacology learning and 15 articles in chemicals. Accordingly in field of pharmacology, AI and ML approaches would be useful to analyze data from many sources, ranging from the chemical structure of a drug to clinical aspects and from genomic informations to disease characteristics. Increasing AI applications in pharmacology is also evident in some studies published on the topic. AI is also useful to predict which chemical structures might bind to a target site. Also, the chemical structure of potent drugs or endogenic factors which used to elucidate the structure of a potential target. Finally, in vivo characteristics of a new compound also can be predicted by understanding drugs pharmacokinetics (PKs), and pharmacodynamics. Later, the toxicity profile of a novel compound could be assessed by AL and ML. which requires substantial datasets with in vivo data provided through clinical studies. Especially chemical structure plays an important role in the occurrence of toxicity, the same approaches as in drug discovery could be applied. Two important toxicities that are assessed during drug development are cardiotoxicity and hepatotoxicity. Conclusion: AI approaches are widely used in all aspects of pharmacology, from drug discovery to real-world evidence and personalized medicine.In recent years, AI is rapidly becoming a standard analytical tool in drug development.
کلمات کلیدی
Artificial Intelligence (AI),Machine Learning (ML), Pharmacology
